A method, device, medium and equipment for detecting wear of a hot-dip galvanizing submerged roll bearing assembly

Abstract

The application provides a wear detection method, device, medium and equipment for a hot galvanizing submerged roll bearing assembly, which comprises the following steps: receiving an initial vibration signal of the submerged roll; performing wavelet decomposition on the initial vibration signal by using a wavelet transform algorithm to obtain wavelet signals of each layer; determining a target layer wavelet signal, determining a surface wear index of the submerged roll bearing assembly based on the target layer wavelet signal; and performing wear detection according to the surface wear index of the submerged roll bearing assembly. When wear occurs on the surface of the bearing bushing sleeve of the submerged roll, the friction coefficient of the contact surface between the bearing bushing and the sleeve will change, thereby exciting friction self-excited vibration of the submerged roll system. Even in the early stage of wear, the precision detection of the surface wear of the submerged roll bearing assembly can be realized through the analysis of the vibration signal of the submerged roll. No mechanical contact with the surface of the submerged roll is needed, thereby reducing the scratch damage to the roll surface and improving the quality of the strip steel surface.

Description

Technical Field

[0001] This invention relates to the field of hot-dip galvanizing equipment testing technology, and in particular to a method, apparatus, medium and equipment for testing the wear of hot-dip galvanizing submerged roller bearing assemblies. Background Technology

[0002] Submerged rollers are used in the zinc pots of hot-dip galvanizing units, and these rollers are submerged below the zinc molten liquid level. The wear condition of the bearing assemblies, such as the bushings and sleeves, of the submerged rollers determines their replacement cycle. Excessive wear can cause the roller shaft to break, leading to unit shutdown due to accidents. Therefore, it is essential to inspect the wear condition of the submerged roller bearing assemblies.

[0003] In related technologies, the wear of the submerged roll bearings and bushings is generally measured indirectly by mechanically contacting the surface of the submerged roll. However, mechanical contact detection methods are prone to creating scratches on the submerged roll surface, leading to severe surface defects in the strip. Furthermore, mechanical contact detection methods determine wear by detecting changes in the outer diameter of the bearing and the inner diameter of the bushing, but these changes only become significant when the wear is substantial. Therefore, existing technologies cannot accurately detect wear in its early stages.

[0004] Based on this, the present invention provides a wear detection method for hot-dip galvanized submerged roller bearing assemblies to solve the above-mentioned problems in the prior art. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a wear detection method, apparatus, medium, and equipment for hot-dip galvanized submerged roller bearing assemblies. This solves or partially solves the technical problems of existing technologies being unable to accurately detect hot-dip galvanized submerged roller bearing assemblies in the early stages of wear, and the tendency to form scratches on the surface of the submerged roller during wear detection, leading to surface defects on the strip steel.

[0006] A first aspect of the present invention provides a wear detection method for a hot-dip galvanized submerged roller bearing assembly, wherein vibration sensors are respectively installed on the drive-side roller arm and the operating-side roller arm of the submerged roller; the method includes: Receive the initial vibration signal of the submerged roller system sent by the vibration sensor; The initial vibration signal was decomposed using a wavelet transform algorithm to obtain wavelet signals at each level. The target layer wavelet signal is determined from the wavelet signals of each layer, and the surface wear index of the submerged roller bearing assembly is determined based on the target layer wavelet signal. Wear detection is performed based on the surface wear index of the submerged roller bearing assembly.

[0007] In the above scheme, the step of using a wavelet transform algorithm to perform wavelet decomposition on the initial vibration signal to obtain wavelet signals at each level includes: The number of decomposition layers is determined. When decomposing the current layer, a low-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the low-frequency signal of the current layer. The low-frequency signal of the current layer is downsampled to obtain the approximation coefficients of the current layer. A high-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the high-frequency signal of the current layer. The high-frequency signal of the current layer is downsampled to obtain the detail coefficients of the current layer. The above decomposition steps are repeated until the detail coefficients corresponding to all layers are obtained; wherein, the wavelet signals of each layer are the detail coefficients of the corresponding layer.

[0008] In the above scheme, determining the target layer wavelet signal from the wavelet signals of each layer includes: Obtain the reference frequency band corresponding to each wavelet signal layer; The reference frequency range corresponding to the self-excited vibration of the submerged roller system is matched one by one with each reference frequency band; The wavelet signal corresponding to the successfully matched reference frequency band is determined as the target layer wavelet signal.

[0009] In the above scheme, determining the surface wear index of the submerged roller bearing assembly based on the wavelet signal of the target layer includes: Determine the root mean square value of the wavelet signal of the target layer; The root mean square value is determined as the surface wear index of the submerged roller bearing assembly.

[0010] In the above scheme, determining the root mean square value of the time-domain vibration signal corresponding to the wavelet signal of the target layer includes: According to the formula Determine the root mean square value of the time-domain vibration signal corresponding to the wavelet signal of the target layer. W ; Among them, the n The total number of sampling points for the time-domain vibration signal, the i The number of the sampling point, the For the first i The vibration amplitude corresponding to each sampling point.

[0011] In the above scheme, the wear detection based on the surface wear index of the submerged roller bearing assembly includes: Determine whether the surface wear index of the submerged roller bearing assembly is greater than or equal to a preset first threshold and less than a second threshold; If so, it indicates that there is slight wear on the submerged roller bearing assembly.

[0012] A second aspect of the present invention provides a wear detection device for a hot-dip galvanized submerged roller bearing assembly, wherein vibration sensors are respectively installed on the drive-side roller arm and the operating-side roller arm of the submerged roller; the device includes: A receiving unit is used to receive the initial vibration signal of the submerged roller system sent by the vibration sensor; The decomposition unit is used to perform wavelet decomposition on the initial vibration signal using a wavelet transform algorithm to obtain wavelet signals at each level. The determining unit is used to determine the target layer wavelet signal from the wavelet signals of each layer, and to determine the surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal. The detection unit is used to perform wear detection based on the surface wear index of the submerged roller bearing assembly.

[0013] In the above scheme, the detection unit is specifically used for: Determine whether the surface wear index of the submerged roller bearing assembly is greater than a preset first threshold; If so, then it is determined that the submerged roller bearing assembly is worn.

[0014] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any of the first aspects.

[0015] A fourth aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method described in any of the first aspects.

[0016] This invention provides a method, apparatus, medium, and equipment for wear detection of a hot-dip galvanized submerged roller bearing assembly. Vibration sensors are respectively installed on the drive-side roller arm and the operating-side roller arm of the submerged roller. The method includes: receiving an initial vibration signal of the submerged roller transmitted by the vibration sensors; performing wavelet decomposition on the initial vibration signal using a wavelet transform algorithm to obtain wavelet signals of various layers; determining a target layer wavelet signal from the wavelet signals of each layer; determining a surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal; and determining the surface wear index of the submerged roller bearing assembly based on the surface wear index. Wear detection is performed on the rolls. Since the roll arms of the submerged roll are connected to the submerged roll bearing bushes, wear on the surface of the submerged roll bearing bushes will cause a change in the friction coefficient of the contact surface between the bearing bushes and bushes, thereby exciting the submerged roll system to generate frictional self-excited vibration. Therefore, even in the early stage of wear, the wear on the surface of the submerged roll bearing assembly can be accurately detected by analyzing the vibration signal of the submerged roll. Furthermore, since this detection method only requires the use of vibration sensors to collect vibration signals and does not require mechanical contact with the surface of the submerged roll, it reduces scratch damage to the roll surface and improves the quality of the strip surface. Attached Figure Description

[0017] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A schematic flowchart of a wear detection method for a hot-dip galvanized submerged roller bearing assembly according to an embodiment of the present invention is shown. Figure 2 A schematic diagram of a submerged roller system according to an embodiment of the present invention is shown; Figure 3 A schematic diagram of the initial vibration signal flow direction according to an embodiment of the present invention is shown; Figure 4 A schematic diagram of an initial vibration signal according to an embodiment of the present invention is shown; Figure 5 A schematic diagram of the frequency range covered by the initial vibration signal according to an embodiment of the present invention is shown; Figure 6 A schematic diagram of the first frequency domain range of the first layer detail coefficients according to an embodiment of the present invention is shown; Figure 7 A schematic diagram of a time-domain vibration signal in a first frequency domain range according to an embodiment of the present invention is shown; Figure 8A schematic diagram of the second frequency domain range of the second layer detail coefficients according to an embodiment of the present invention is shown; Figure 9 A schematic diagram of a time-domain vibration signal in a second frequency domain range according to an embodiment of the present invention is shown; Figure 10 A schematic diagram of the third frequency domain range of the third layer detail coefficients according to an embodiment of the present invention is shown; Figure 11 A schematic diagram of a time-domain vibration signal in a third frequency domain range according to an embodiment of the present invention is shown; Figure 12 A schematic diagram of the fourth frequency domain range of the fourth layer detail coefficients according to an embodiment of the present invention is shown; Figure 13 A schematic diagram of a time-domain vibration signal in a fourth frequency domain range according to an embodiment of the present invention is shown; Figure 14 A schematic diagram of the fourth frequency domain range of the fifth layer detail coefficients according to an embodiment of the present invention is shown; Figure 15 A schematic diagram of a time-domain vibration signal in the fifth frequency domain range according to an embodiment of the present invention is shown; Figure 16 A schematic diagram of a wear detection device for a hot-dip galvanized submerged roller bearing assembly according to an embodiment of the present invention is shown. Detailed Implementation

[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0019] This invention provides a wear detection method for hot-dip galvanized submerged roller bearing assemblies, such as... Figure 1 As shown, the method includes the following steps: S110, receiving the initial vibration signal of the submerged roller system sent by the vibration sensor.

[0020] To better understand the technical solution of this invention, the submerged roller system will be introduced first, such as... Figure 2As shown, the submerged roller system includes: a submerged roller 21, roller arms (including a drive-side roller arm 22 and an operating-side roller arm 23), and a bearing assembly. The bearing assembly is generally installed at the end of the submerged roller, and the roller arm is connected to the submerged roller through the bearing assembly. Since both the bearing assembly and the submerged roller are located underwater in the molten zinc during operation, the present invention installs corresponding vibration sensors 24 on the drive-side roller arm 22 and the operating-side roller arm 23 respectively to collect the initial vibration signals of the drive side and the operating side.

[0021] like Figure 3 As shown, after the vibration sensor acquires the initial vibration signal, it sends the initial vibration signal as a 4-20mA current signal to the vibration data acquisition unit 31. The vibration data acquisition unit then sends the initial vibration signal to the wear detection device 32 of the hot-dip galvanized submerged roller bearing assembly. The detection device can then receive the initial vibration signal of the submerged roller system sent by the vibration sensor. Data transmission between the vibration data acquisition unit 31 and the detection device is performed via the TCP / IP protocol. The detection device can be a computer device or processor with data processing and analysis functions; no limitation is imposed here.

[0022] Since the roller arms of the submerged roller are connected to the submerged roller bearing bushes, wear on the surface of the submerged roller bearing bushes will cause a change in the coefficient of friction of the contact surface between the bearing bushes and bushes, which will excite the submerged roller system to generate frictional self-excited vibration (if there is no friction, there will be no self-excited vibration). The vibration frequency of the self-excited vibration is the natural frequency, which depends on the mechanical structure of the submerged roller system (and is less affected by the production process). Therefore, even in the early stage of wear, the wear on the surface of the submerged roller bearing assembly can be accurately detected by frequency domain analysis of the vibration signal of the submerged roller, so as to determine the wear condition of the bearing bush surface in a timely manner.

[0023] Generally, the reference frequency range corresponding to the self-excited vibration of the submerged roller system is 80~110Hz.

[0024] S111, the initial vibration signal is decomposed into wavelet signals using a wavelet transform algorithm to obtain wavelet signals of each layer.

[0025] Both the initial vibration signals from the drive side and the operating side can be decomposed using wavelet transform algorithms to obtain wavelet signals at various levels. Each wavelet signal level contains time-domain vibration signals within a corresponding frequency band, and the frequency bands corresponding to each wavelet signal level are different.

[0026] In one implementation, the initial vibration signal is decomposed using a wavelet transform algorithm to obtain wavelet signals at each level, including: The number of decomposition layers is determined. When decomposing the current layer, a low-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the low-frequency signal of the current layer. The low-frequency signal of the current layer is downsampled to obtain the approximation coefficients of the current layer. A high-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the high-frequency signal of the current layer. The high-frequency signal of the current layer is downsampled to obtain the detail coefficients of the current layer. Repeat the above decomposition steps until the detail coefficients corresponding to all layers are obtained; where the wavelet signals of each layer are the detail coefficients of the corresponding layer.

[0027] Specifically, this invention uses the db7 wavelet basis for 5-level decomposition (5 decomposition levels) to finally obtain the time-domain vibration signal in the corresponding frequency band. Since the db7 wavelet basis contains low-pass and high-pass filters, after wavelet decomposition, each level of wavelet decomposition will simultaneously output low-frequency and high-frequency signals. The frequencies of the low-frequency signals obtained after different levels of wavelet decomposition are different, and the frequencies of the high-frequency signals obtained after different levels of wavelet decomposition are also different.

[0028] The specific breakdown is as follows: like Figure 4 and Figure 5 As shown, Figure 4 This is a schematic diagram of the initial vibration signal. Figure 5 The initial vibration signal covers the frequency range, which is the full frequency range. In the subsequent decomposition process, the full frequency range will be decomposed into sub-frequency bands at different levels.

[0029] The initial vibration signal is decomposed into its first layer to obtain the first layer wavelet signal: In the first-level decomposition, a low-pass filter is used to convolve the initial vibration signal to obtain the first-level low-frequency signal. This first-level low-frequency signal is then downsampled by a factor of 2, retaining only even-numbered points, resulting in a first signal sequence of length L / 2. This first signal sequence represents the first-level approximation coefficients. A high-pass filter is then used to convolve the initial vibration signal to obtain the first-level high-frequency signal. This first-level high-frequency signal is then downsampled by a factor of 2 to obtain a second signal sequence of length L / 2. This second signal sequence represents the first-level detail coefficients. The first-level detail coefficients constitute the first-level wavelet signal. The first frequency domain range of the first layer detail coefficients is as follows: Figure 6 As shown, the time-domain vibration signal in the first frequency domain range Figure 7 As shown.

[0030] The first-level approximation coefficients are decomposed into a second-level wavelet signal: In the second-level decomposition, a low-pass filter is used to convolve the first-level approximation coefficients to obtain the second-level low-frequency signal. The second-level low-frequency signal is then downsampled by a factor of 2, retaining only even-numbered points, to obtain a third signal sequence of length L / 4, which is the second-level approximation coefficient. A high-pass filter is used to convolve the first-level approximation coefficients to obtain the second-level high-frequency signal. The second-level high-frequency signal is then downsampled by a factor of 2 to obtain a fourth signal sequence of length L / 4, which is the second-level detail coefficient.

[0031] The second frequency domain range of the second layer detail coefficients is as follows: Figure 8 As shown, the time-domain vibration signal in the second frequency domain range Figure 9 As shown.

[0032] The second-level approximation coefficients are decomposed into a third-level wavelet signal: In the third-level decomposition, a low-pass filter is used to convolve the second-level approximation coefficients to obtain the third-level low-frequency signal. Then, the third-level low-frequency signal is downsampled by a factor of 2, retaining only even-numbered points, to obtain a fifth signal sequence of length L / 8, which is the third-level approximation coefficient. A high-pass filter is used to convolve the second-level approximation coefficients to obtain the third-level high-frequency signal. The third-level high-frequency signal is downsampled by a factor of 2 to obtain a sixth signal sequence of length L / 8, which is the third-level detail coefficient.

[0033] The third frequency domain range of the third layer detail coefficients is as follows: Figure 10 As shown, the time-domain vibration signal in the third frequency domain range Figure 11 As shown.

[0034] The third-level approximation coefficients are decomposed into a fourth-level wavelet signal: In the fourth-level decomposition, a low-pass filter is used to convolve the third-level approximation coefficients to obtain the fourth-level low-frequency signal. Then, the fourth-level low-frequency signal is downsampled by a factor of 2, retaining only even-numbered points, to obtain a seventh signal sequence of length L / 16, which is the fourth-level approximation coefficient. A high-pass filter is used to convolve the third-level approximation coefficients to obtain the fourth-level high-frequency signal. The fourth-level high-frequency signal is downsampled by a factor of 2 to obtain an eighth signal sequence of length L / 16, which is the fourth-level detail coefficient.

[0035] Among them, the fourth frequency domain range of the fourth layer detail coefficients is as follows: Figure 12 As shown, the time-domain vibration signal in the fourth frequency domain range Figure 13 As shown.

[0036] The fifth level decomposition is performed on the fourth level approximation coefficients to obtain the fifth level wavelet signal: In the fifth-level decomposition, a low-pass filter is used to convolve the fourth-level approximation coefficients to obtain the fifth-level low-frequency signal. Then, the fifth-level low-frequency signal is downsampled by a factor of 2, retaining only even-numbered points, to obtain a ninth signal sequence of length L / 32, which is the fourth-level approximation coefficient. A high-pass filter is used to convolve the fourth-level approximation coefficients to obtain the fifth-level high-frequency signal. The fifth-level high-frequency signal is downsampled by a factor of 2 to obtain a tenth signal sequence of length L / 32, which is the fifth-level detail coefficient.

[0037] Among them, the fifth frequency domain range of the fifth layer detail coefficients is as follows: Figure 14 As shown, the time-domain vibration signal in the fifth frequency domain range Figure 15 As shown.

[0038] This decomposes the initial vibration signal into five wavelet signals. It is worth noting that the wavelet signals are not pure frequency domain signals, but joint time-frequency domain signals, which retain both the time dimension distribution and the frequency domain distribution.

[0039] After being decomposed into 5 wavelets, the remaining signal in the original vibration signal is the wavelet signal of the 0th layer.

[0040] S112, determine the target layer wavelet signal from the wavelet signals of each layer, and determine the surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal.

[0041] Since the submerged roller system has a natural frequency range when it undergoes self-excited vibration, the natural frequency range can be estimated by establishing a finite element model of the submerged roller system and calculating the finite element model.

[0042] Therefore, the inherent frequency range can be used as the reference frequency range. Based on the reference frequency range, the target layer wavelet signal needs to be determined from the wavelet signals of each layer. Based on the target layer wavelet signal, the surface wear index of the submerged roller bearing assembly is determined. The frequency range of the target layer wavelet signal is consistent with the inherent frequency range.

[0043] In one implementation, determining the target layer wavelet signal from the wavelet signals of each layer includes: Obtain the reference frequency band corresponding to each wavelet signal layer; The reference frequency range corresponding to the self-excited vibration of the submerged roller system is matched one by one with each reference frequency band; The wavelet signal corresponding to the successfully matched reference frequency band is determined as the target layer wavelet signal.

[0044] Specifically, since the frequency band corresponding to each layer of wavelet signal is different, with an inherent frequency range of 80~110Hz, the inherent frequency range can be matched with the frequency band corresponding to each layer of wavelet signal. The wavelet signal that is successfully matched is the target layer wavelet signal.

[0045] In this invention, the target layer wavelet signal is the third layer wavelet signal.

[0046] Once the target layer wavelet signal is determined, the surface wear index of the submerged roller bearing assembly can be determined based on the target layer wavelet signal, including: Determine the root mean square value of the wavelet signal at the target layer; The root mean square value was determined as the surface wear index of the submerged roller bearing assembly.

[0047] In one implementation, determining the root mean square value of the time-domain vibration signal corresponding to the target layer wavelet signal includes: According to the formula Determine the root mean square value of the time-domain vibration signal corresponding to the wavelet signal of the target layer. W ; in, n This represents the total number of sampling points for the time-domain vibration signal. i The sampling point number is... For the first i The vibration amplitude corresponding to each sampling point.

[0048] For example, refer to Figure 11 It can Figure 11 The root mean square value is obtained by calculating the vibration amplitude at all sampling points. M The root mean square value was determined as the surface wear index of the submerged roller bearing assembly.

[0049] S113, wear detection is performed based on the surface wear index of the submerged roller bearing assembly.

[0050] After the surface wear index of the submerged roller bearing assembly is determined, wear testing is performed based on the surface wear index, including: Determine whether the surface wear index of the submerged roller bearing assembly is greater than a preset first threshold and less than a second threshold; If so, it indicates that there is slight wear on the submerged roller bearing assembly.

[0051] Different thresholds correspond to different degrees of wear. For example, if there is slight wear, the first threshold can be 0.5; if there is moderate wear, the second threshold can be 0.7; and if there is severe wear, the third threshold can be 1.

[0052] Therefore, when the surface wear index of the submerged roll bearing assembly is greater than or equal to the first threshold and less than the second threshold, it indicates that the surface of the submerged roll bearing assembly has slight wear; if the surface wear index of the submerged roll bearing assembly is greater than or equal to the second threshold and less than the third threshold, it indicates that the surface of the submerged roll bearing assembly has moderate wear. At this time, it is necessary to adjust the production process to avoid quality defects on the strip surface.

[0053] If the surface wear index of the submerged roll bearing assembly is greater than or equal to the third threshold, it indicates that the surface of the submerged roll bearing assembly is severely worn and the submerged roll needs to be replaced.

[0054] By analyzing the vibration signals generated by the frictional self-excited vibration of the submerged roll system, different degrees of wear can be accurately analyzed. Even slight wear in the early stages of wear can be accurately detected by analyzing the vibration signals of the submerged roll. Furthermore, the detection method only requires the use of vibration sensors to collect vibration signals, without the need for mechanical contact with the surface of the submerged roll, thereby reducing scratch damage to the roll surface and improving the quality of the strip surface.

[0055] Based on the same inventive concept as in the foregoing embodiments, this embodiment also provides a wear detection device for a hot-dip galvanized submerged roller bearing assembly, wherein vibration sensors are respectively installed on the drive-side roller arm and the operating-side roller arm of the submerged roller; such as Figure 16 As shown, the device includes: The receiving unit 161 is used to receive the initial vibration signal of the submerged roller system sent by the vibration sensor; Decomposition unit 162 is used to perform wavelet decomposition on the initial vibration signal using a wavelet transform algorithm to obtain wavelet signals of each layer. The determining unit 163 is used to determine the target layer wavelet signal from the wavelet signals of each layer, and to determine the surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal. The detection unit 164 is used to perform wear detection based on the surface wear index of the submerged roller bearing assembly.

[0056] In one embodiment, the detection unit 164 is specifically used for: Determine whether the surface wear index of the submerged roller bearing assembly is greater than a preset first threshold; If so, then it is determined that the submerged roller bearing assembly is worn.

[0057] Since the apparatus described in this embodiment of the invention is used for implementing the wear detection method of the hot-dip galvanized submerged roller bearing assembly of this invention, those skilled in the art can understand the specific structure and variations of the apparatus based on the method described in this embodiment of the invention, and therefore will not be repeated here. All apparatuses used in the methods of this embodiment of the invention fall within the scope of protection of this invention.

[0058] Based on the same inventive concept, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any step of the method described above.

[0059] Based on the same inventive concept, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0060] Through one or more embodiments of the present invention, the present invention has the following beneficial effects or advantages: This invention provides a method, apparatus, medium, and equipment for wear detection of a hot-dip galvanized submerged roller bearing assembly. Vibration sensors are respectively installed on the drive-side roller arm and the operating-side roller arm of the submerged roller. The method includes: receiving an initial vibration signal of the submerged roller transmitted by the vibration sensors; performing wavelet decomposition on the initial vibration signal using a wavelet transform algorithm to obtain wavelet signals of various layers; determining a target layer wavelet signal from the wavelet signals of each layer; determining a surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal; and determining the surface wear index of the submerged roller bearing assembly based on the surface wear index. Wear detection is performed on the rolls. Since the roll arms of the submerged roll are connected to the submerged roll bearing bushes, wear on the surface of the submerged roll bearing bushes will cause a change in the friction coefficient of the contact surface between the bearing bushes and bushes, thereby exciting the submerged roll system to generate frictional self-excited vibration. Therefore, even in the early stage of wear, the wear on the surface of the submerged roll bearing assembly can be accurately detected by analyzing the vibration signal of the submerged roll. Furthermore, since this detection method only requires the use of vibration sensors to collect vibration signals and does not require mechanical contact with the surface of the submerged roll, it reduces scratch damage to the roll surface and improves the quality of the strip surface.

[0061] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0062] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0063] Similarly, it should be understood that, in order to simplify this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0064] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0065] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0066] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components of the gateway, proxy server, or system according to embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0067] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0068] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting wear of a hot-dip galvanized submerged roller bearing assembly, characterized in that, Vibration sensors are respectively installed on the drive side roller arm and the operating side roller arm of the submerged roller; the method includes: Receive the initial vibration signal of the submerged roller system sent by the vibration sensor; The initial vibration signal was decomposed into wavelet signals of each layer using a wavelet transform algorithm. The target layer wavelet signal is determined from the wavelet signals of each layer, and the surface wear index of the submerged roller bearing assembly is determined based on the target layer wavelet signal. Wear detection is performed based on the surface wear index of the submerged roller bearing assembly.

2. The method as described in claim 1, characterized in that, The initial vibration signal is decomposed using a wavelet transform algorithm to obtain wavelet signals at each level, including: The number of decomposition layers is determined. When decomposing the current layer, a low-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the low-frequency signal of the current layer. The low-frequency signal of the current layer is downsampled to obtain the approximation coefficients of the current layer. A high-pass filter is used to convolve the approximation coefficients output from the previous layer to obtain the high-frequency signal of the current layer. The high-frequency signal of the current layer is downsampled to obtain the detail coefficients of the current layer. The above decomposition steps are repeated until the detail coefficients corresponding to all layers are obtained; wherein, the wavelet signals of each layer are the detail coefficients of the corresponding layer.

3. The method as described in claim 1, characterized in that, Determining the target layer wavelet signal from the wavelet signals of each layer includes: Obtain the reference frequency band corresponding to each wavelet signal layer; The reference frequency range corresponding to the self-excited vibration of the submerged roller system is matched one by one with each reference frequency band; The wavelet signal corresponding to the successfully matched reference frequency band is determined as the target layer wavelet signal.

4. The method as described in claim 1, characterized in that, The determination of the surface wear index of the submerged roller bearing assembly based on the wavelet signal of the target layer includes: Determine the root mean square value of the wavelet signal of the target layer; The root mean square value is determined as the surface wear index of the submerged roller bearing assembly.

5. The method as described in claim 1, characterized in that, Determining the root mean square value of the time-domain vibration signal corresponding to the wavelet signal of the target layer includes: According to the formula Determine the root mean square value of the time-domain vibration signal corresponding to the wavelet signal of the target layer. W ; Among them, the n The total number of sampling points for the time-domain vibration signal, the i The number of the sampling point, the For the first i The vibration amplitude corresponding to each sampling point.

6. The method as described in claim 1, characterized in that, The wear detection based on the surface wear index of the submerged roller bearing assembly includes: Determine whether the surface wear index of the submerged roller bearing assembly is greater than or equal to a preset first threshold and less than a second threshold; If so, it indicates that there is slight wear on the submerged roller bearing assembly.

7. A wear detection device for a hot-dip galvanized submerged roller bearing assembly, characterized in that, Vibration sensors are respectively installed on the drive side roller arm and the operating side roller arm of the submerged roller; the device includes: A receiving unit is used to receive the initial vibration signal of the submerged roller system sent by the vibration sensor; The decomposition unit is used to perform wavelet decomposition on the initial vibration signal using a wavelet transform algorithm to obtain wavelet signals at each level. The determining unit is used to determine the target layer wavelet signal from the wavelet signals of each layer, and to determine the surface wear index of the submerged roller bearing assembly based on the target layer wavelet signal. The detection unit is used to perform wear detection based on the surface wear index of the submerged roller bearing assembly.

8. The apparatus as claimed in claim 7, characterized in that, The detection unit is specifically used for: Determine whether the surface wear index of the submerged roller bearing assembly is greater than a preset first threshold; If so, then it is determined that the submerged roller bearing assembly is worn.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-6.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1-6.

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